This invention relates generally to wireless communication systems and more particularly to channel capacity and power management in variable rate data transmission systems transmitting over a fixed-bandwidth communication channel.
The invention finds application in prior art radio frequency communication systems operating over one or more communication channels of fixed bandwidth. When such systems are used for data communication, they may be configured to communicate data at a predetermined data rate, modulation format, error-correction-coding, and other transmit waveform characteristics that determine the so called “common air interface” of the radio frequency communication system.
The transmit waveform and the prevailing additive noise in the channel determine the capacity of the channel for carrying information. In selecting the transmit waveform characteristics, it is usually the objective of the network service provider to provide an installed channel capacity that is sufficient to meet the peak traffic load, which may be characterized by an average source data rate. It is also an objective of the network service provider to guarantee a minimum error performance at the message destination. The destination error performance is usually measured by metrics such as bit error rate or message error rate. Shannon's theory lays down the theoretical foundation of a quantitative measure of channel capacity asC=B[1+(S/N)]  (1)C: channel capacity in bits/second (bps)B: channel bandwidth in HzS: received signal power in wattsN: received noise power in watts in the detection bandwidthIt is known [Carlson, A. B., Communication Systems: An Introduction to Signals and Noise in Electrical Communications, Mc-Graw-Hill, 1968, p. 354] that the Shannon capacity theorem leads to the following relationship between the minimum required Eb/N0 and the average source data rate, R:Eb/N0=[2(R/B)−1]/[R/B]  (2)where Eb/N0 is the ratio of the received signal energy per bit of information to the single-sided nose power spectral density.
FIG. 1 shows a plot of equation (2). This plot shows the theoretical limit of minimum Eb/N0 for a given R/B ratio, as well as the Eb/N0 required by a number of practical prior art coding and modulation schemes. As shown in the plot, the right-half plane is referred to as the bandwidth limited region, where R/B tends to infinity, indicating that indefinitely high data rates can be accommodated with a fixed bandwidth channel but at the expense of indefinitely high transmit power, or Eb/N0. In contrast, the left-half plane is referred to as the power limited region, where Eb/N0 can be reduced down to a theoretical limit of −1.6 dB in exchange of very high channel bandwidths for a given R, or vanishingly small R/B ratios.
According to Shannon's theory, as long as the Eb/N0 is above that given by equation (2), for a given ratio of (R/B), error free communication is possible. While Shannon's theorem indicated the ultimate performance bound for a communication system, it did not indicate the specific means of achieving, or approaching, the ultimate performance. It has been the objective of communication system designers to invent specific, practical means for approaching the Shannon capacity.
A noteworthy feature of FIG. 1 is that moving toward the left extremity of the graph, that is operating at very low Eb/N0 with low R/B, requires increasingly complex error-correction coding schemes, referred to here simply as “coding schemes”, such as low rate convolutional coding with sequential decoding. In contrast, moving toward the right extremity of the graph requires the use of more complex modulation schemes, such as multilevel PSK modulation, referred to as MPSK, where the number of levels, M, typically takes on values of 2n, that is 2, 4, 8, 16, an so on.
Independent of Shannon theory, another theoretical limitation governs high speed data transmission through band-limited channels; this limitation is defined by Nyquist theory. Nyquist theory states that the maximum symbol rate of a bandlimited channel, of bandpass, bandwidth B Hz, or lowpass equivalent bandwidth B/2 Hz, is B symbols/second. For example, using 6 kHz spaced mobile satellite channel, the maximum symbol rate supportable by such a channel is 6000 symbols/second.
Before considering the implication of Nyquist theory, it is useful, first, to review the formal definition of a symbol, or channel symbol, in digital communication systems. A symbol is a waveform of finite duration, belonging to a set of finite size, where each member of the set carries a predetermined number of bits of information. For example, 8PSK symbols are sine waves of a fixed amplitude and variable phase, where the phase can take one of 8 values. By virtue of the 8 possible phases of each 8PSK symbol, 3 bits of information are carried by each 8PSK symbol. If error-correction coding is used, the number of bits of information conveyed by each symbols is reduced by a redundancy factor equal to the coding rate.
Returning to the discussion of Nyquist theory, any attempt to transmit symbols at a rate higher than the Nyquist rate of B symbols/second, where B is the bandpass channel bandwidth, results in intersymbol interference, wherein the decision process for detecting the bits carried by each symbol is affected by the energy in adjacent symbols. It is extremely difficult if not practically impossible to transmit symbols through a bandlimited channel at the Nyquist rate as it requires the use of ideal channel filters of bandpass bandwidth B Hz, or lowpass equivalent bandwidth B/2 Hz, having infinitely sharp spectral roll-off. Such filters are referred to as a “brick wall” filters and are physically unrealizable. However, it is practically feasible to approach the Nyquist transmission rate with minimal intersymbol interference by using physically realizable, transmit and receive filters having a particular transfer function referred to as the Nyquist response, known in the prior art. Such Nyquist filters have finite spectral roll-off characteristics and lowpass-equivalent bandwidths that are greater than the B/2-Hz lowpass-equivalent bandwidth of the ideal, brick wall, filter. The excess bandwidth, of a practical Nyquist filter, expressed as a ratio relative to the bandwidth of the ideal brick wall filter, is an important parameter in the design of high speed data transmission systems through bandlimited channels. For example, if W is the bandwidth of L a practical Nyquist filter, the excess bandwidth factor is given by [{W−(B/2)}/(B/2)]. Typical excess bandwidth factors of practical systems range from 100% to 50%. Clearly, the lower the excess bandwidth factor, the greater is the symbol rate for a channel of given bandwidth.
Prior art communication systems have not been known to use transmitter power, modulation format or error-correction coding in a dynamic manner, to match the channel capacity to the average source data rate. Most often, a fixed channel capacity is installed, matched to the expected peak traffic load, leading to the existence of underutilized capacity during off-peak times. Some instances are known, however, such as “bandwidth on demand” systems, where channel bandwidth is used dynamically to accommodate time varying traffic.
In most communication systems, message traffic does not flow at a constant level. To the contrary, it is well known, and observed in most communication applications, that message traffic is sporadic, and typically cyclic over a day's period. Current systems appear to be deficient in ways of dynamically matching the channel capacity in general and transmit power in particular to actual, time variable traffic demands on the systems. Many satellite communication systems use leased space segment capacity, whereby satellite channels are leased from the satellite owner at a price determined by the amount of power and bandwidth used. For such systems, operating costs on a “per kilobyte of traffic” basis typically reflect power usage at maximum traffic loads and are, consequently, higher than necessary because of inherent inflexibilities in adjusting the power levels and other aspects of the transmit waveform to the traffic loads on such systems.